A comparison of mixture toxicity assessment: examining the chronic toxicity of atrazine, permethrin and chlorothalonil in mixtures to Ceriodaphnia cf. dubia

Pesticides predominantly occur in aquatic ecosystems as mixtures of varying complexity, yet relatively few studies have examined the toxicity of pesticide mixtures. Atrazine, chlorothalonil and permethrin are widely used pesticides that have different modes of action. This study examined the chronic toxicities (7-d reproductive impairment) of these pesticides in binary and ternary mixtures to the freshwater cladoceran Ceriodaphnia cf. dubia. The toxicity of the mixtures was compared to that predicted by the independent action (IA) model for mixtures, as this is the most appropriate model for chemicals with different modes of action. Following this they were compared to the toxicity predicted by the concentration addition (CA) model for mixtures. According to the IA model, the toxicity of the chlorothalonil plus atrazine mixture conformed to antagonism, while that of chlorothalonil and permethrin conformed to synergism. The toxicity of the atrazine and permethrin mixture as well as the ternary mixture conformed to IA implying there was either no interaction between the components of these mixtures and/or in the case of the ternary mixture the interactions cancelled each other out to result in IA. The synergistic and antagonistic mixtures deviated from IA by factors greater than 3 and less than 2.5, respectively. When the toxicity of the mixtures was compared to the predictions of the CA model, the binary mixture of chlorothalonil plus atrazine, permethrin plus atrazine and the ternary mixture all conformed to antagonism, while the binary mixture of chlorothalonil plus permethrin conformed to CA. Using the CA model provided estimates of mixture toxicity that did not markedly underestimate the measured toxicity, unlike the IA model, and therefore the CA model is the most suitable to use in ecological risk assessments of these pesticides.     

Assessing joint toxicity of chemicals in Enchytraeus albidus (Enchytraeidae) and Porcellionides pruinosus (Isopoda) using avoidance behaviour as an endpoint

Contamination problems are often characterized by complex mixtures of chemicals. There are two conceptual models usually used to evaluate patterns of mixture toxicity: Concentration Addition (CA) and Independent Action (IA). Deviations from these models as synergism, antagonism and dose dependency also occur. In the present study, single and mixture toxicity of atrazine, dimethoate, lindane, zinc and cadmium were tested in Porcellionides pruinosus and Enchytraeus albidus, using avoidance as test parameter. For both species patterns of antagonism were found when exposed to dimethoate and atrazine, synergism for lindane and dimethoate exposures (with the exception of lower doses in the isopod case study) and concentration addition for cadmium and zinc occurred, while the exposure to cadmium and dimethoate showed dissimilar patterns.This study highlights the importance of dose dependencies when testing chemical mixtures and that avoidance tests can also be used to asses the effects of mixture toxicity.     

Paradigm lost, paradigm found: the re-emergence of hormesis as a fundamental dose response model in the toxicological sciences

This paper provides an assessment of the toxicological basis of the hormetic dose-response relationship including issues relating to its reproducibility, frequency, and generalizability across biological models, endpoints measured and chemical class/physical stressors and implications for risk assessment. The quantitative features of the hormetic dose response are described and placed within toxicological context that considers study design, temporal assessment, mechanism, and experimental model/population heterogeneity. Particular emphasis is placed on an historical evaluation of why the field of toxicology rejected hormesis in favor of dose response models such as the threshold model for assessing non-carcinogens and linear no threshold (LNT) models for assessing carcinogens. The paper argues that such decisions were principally based on complex historical factors that emerged from the intense and protracted conflict between what is now called traditional medicine and homeopathy and the overly dominating influence of regulatory agencies on the toxicological intellectual agenda. Such regulatory agency influence emphasized hazard/risk assessment goals such as the derivation of no observed adverse effect levels (NOAELs) and the lowest observed adverse effect levels (LOAELs) which were derived principally from high dose studies using few doses, a feature which restricted perceptions and distorted judgments of several generations of toxicologists concerning the nature of the dose-response continuum. Such historical and technical blind spots lead the field of toxicology to not only reject an established dose-response model (hormesis), but also the model that was more common and fundamental than those that the field accepted.     

A review of toxicity and mechanisms of individual and mixtures of heavy metals in the environment

The rational for the study was to review the literature on the toxicity and corresponding mechanisms associated with lead (Pb), mercury (Hg), cadmium (Cd), and arsenic (As), individually and as mixtures, in the environment. Heavy metals are ubiquitous and generally persist in the environment, enabling them to biomagnify in the food chain. Living systems most often interact with a cocktail of heavy metals in the environment. Heavy metal exposure to biological systems may lead to oxidation stress which may induce DNA damage, protein modification, lipid peroxidation, and others. In this review, the major mechanism associated with toxicities of individual metals was the generation of reactive oxygen species (ROS). Additionally, toxicities were expressed through depletion of glutathione and bonding to sulfhydryl groups of proteins. Interestingly, a metal like Pb becomes toxic to organisms through the depletion of antioxidants while Cd indirectly generates ROS by its ability to replace iron and copper. ROS generated through exposure to arsenic were associated with many modes of action, and heavy metal mixtures were found to have varied effects on organisms. Many models based on concentration addition (CA) and independent action (IA) have been introduced to help predict toxicities and mechanisms associated with metal mixtures. An integrated model which combines CA and IA was further proposed for evaluating toxicities of non-interactive mixtures. In cases where there are molecular interactions, the toxicogenomic approach was used to predict toxicities. The high-throughput toxicogenomics combines studies in genetics, genome-scale expression, cell and tissue expression, metabolite profiling, and bioinformatics.     

A new effect residual ratio (ERR) method for the validation of the concentration addition and independent action models

Background, aim, and scope  

Glutaraldehyde (GA) often acts as an effective sterilant, disinfectant, and preservative in chemical products. It was found that GA had clearly acute toxicity to aquatic organisms. Furthermore, GA in natural environment could not exist as single species but as complex mixtures. To explore the toxicity interaction between GA and the other environmental pollutant, it is necessary to determine the mixture toxicities of various binary mixtures including GA. Two reference models, concentration addition (CA) and independent action (IA), are often employed to evaluate the mixture toxicity, which can be finished by comparing the concentration–response curves (CRCs) predicted by the reference models with the experimental CRC of the mixture. However, the CRC-based method cannot effectively denote the degree of the deviations from the reference models, especially at very low effect levels. Though the model deviation ratio (MDR) can be used to quantitatively evaluate the deviation of a mixture at EC50 level from the reference model, it is difficult to evaluate the deviations at the lower effect levels. Therefore, the primary aim of this study was to develop a new effect residual ratio (ERR) method to validate the deviations from the reference models at various effect levels.     

Hormesis and plant biology

A database has been developed that demonstrates experimental evidence of hormesis. It includes information from a broad range of biological models, including plants, and information on study design, dose-response features, and physical/chemical properties of the agents. An assessment of plant hormetic dose responses is presented based on greater than 3000 plant endpoints. Plant hormetic dose responses were observed for numerous endpoints including disease incidence, reproductive indices, mutagenic endpoints, various metabolic parameters, developmental processes, and a range of growth indicators. Quantitative features of these dose responses typically display a maximum stimulatory response less than two-fold greater than controls and a width of the stimulatory response usually less than 10-fold in dose range. The database establishes that hormetic dose responses commonly occur in plants, are broadly generalizable, and have quantitative features similar to hormetic dose responses found for animals.     

化学物质对发光菌的联合毒性评价方法

毒性单位法(TU)的理论基础来源于剂量加和模型(DA),目前仅在二元联合毒性评价中广泛应用。为了确定TU模型适合评价的混合物类型,实验选取5种剂量效应曲线类型不同的物质,采用微板光度计测试了一元、二元混合物对发光菌青海弧菌-Q67(Vibrio-qinghaiensis sp.-Q67)的急性毒性。根据物质的剂量效应曲线形状将物质分为A、B、C 3类,利用毒性单位法(TU)和联合作用定义法分别对AA类、AB类、AC类、BC类混合物进行分析。结果表明,TU法仅适合于由剂量效应曲线接近直线的物质组成的混合物进行联合毒性的评价。以效应为基准、TU模型为框架建立了TU’模型,该模型可以满足对任何类型已知成分的混合物或者未知成分的实际水样之间的多元联合作用的评价。     

The interaction effects of binary mixtures of benzene and toluene on the developing heart of medaka (Oryzias latipes)

The United States Environmental Protection Agency (USEPA) has pursued the estimation of risk of adverse health effects from exposure to chemical mixtures since the early 1980s. Methods used to calculate risk estimates of mixtures were often based on single chemical information that required assumptions of dose-addition or response-addition and did not consider possible changes in response due to interaction effects among chemicals. Full factorial designs for laboratory studies can produce interactions information, but these are expensive to perform and may not provide the information needed to evaluate specific environmentally relevant mixtures. In this research, groups of Japanese medaka (Oryzias latipes) embryos were exposed to binary mixtures of benzene and toluene as well as to each of these chemicals alone. Endpoint specific dose-response models were built for the hydrocarbon mixture under an assumption of dose-additivity, using the single chemical dose-response information on benzene and toluene. The endpoints included heart rate, heart rate progression, and lethality. Results included a synergistic response for heart rate at 72 h of development, and either additivity or antagonism for all other endpoints at 96 h of development. This work uses an established statistical method to evaluate the toxicity of an environmentally relevant mixture to ascertain whether interaction effects are occurring, thus providing additional information on toxicity.     

Evaluation on the toxicity of ionic liquid mixture with antagonism and synergism to Vibrio qinghaiensis sp.-Q67

Ionic liquids (ILs) are a fascinating group of new chemicals with the potential to replace the classical volatile organic solvents, stimulating many applications in chemical industry. In case ILs are released to the environment, possible combined toxicity should be taken into account and it is, however, often neglected up to now. In this paper, therefore, the concentration-response curves (CRCs) of four groups of IL mixtures with various mixture ratios to Vibrio qinghaiensis sp.-Q67 were determined using the microplate toxicity analysis and were compared to the CRCs predicted by an additive reference model, the concentration addition (CA) or independent action (IA), to identify the toxicity interaction. It is showed that most of the IL mixture rays displayed the classical addition while the remaining rays exhibited antagonism or synergism. Moreover, it is found that the pEC₅₀ values of the mixture rays exhibiting antagonism or synergism are well correlated with the mixture ratio of a certain IL therein.     

Quantification of joint effect for hydrogen bond and development of QSARs for predicting mixture toxicity

A QSAR model is successfully proposed to predict the toxicity effect on Photobacterium phosphoreum by nonpolar-narcotic-chemical mixtures and/or polar-narcotic-chemical mixtures. For nonpolar-narcotic-chemical mixtures and polar-narcotic-chemical mixtures, their corresponding hydrophobicity-based QSAR models are derived from regression analysis. Comparison of these two QSAR models make us believe that it is the joint effect of hydrogen bond in polar-narcotic-chemical mixture that leads to the difference between these two models. Such joint effect of hydrogen bond can be quantified as AMH and BMH by using the different partition coefficients of mixtures in various organic phase/water systems. And the regression analysis results convinced us that the introduction of AMH does improve the quality of the QSAR model with r2=0.948, S.E.=0.166 and F=745.201 at P=0.000 for total 84 mixtures.     

Assessment of combined antiandrogenic effects of binary parabens mixtures in a yeast-based reporter assay

To date, toxicological studies of endocrine disrupting chemicals (EDCs) have typically focused on single chemical exposures and associated effects. However, exposure to EDCs mixtures in the environment is common. Antiandrogens represent a group of EDCs, which draw increasing attention due to their resultant demasculinization and sexual disruption of aquatic organisms. Although there are a number of in vivo and in vitro studies investigating the combined effects of antiandrogen mixtures, these studies are mainly on selected model compounds such as flutamide, procymidone, and vinclozolin. The aim of the present study is to investigate the combined antiandrogenic effects of parabens, which are widely used antiandrogens in industrial and domestic commodities. A yeast-based human androgen receptor (hAR) assay (YAS) was applied to assess the antiandrogenic activities of n-propylparaben (nPrP), iso-propylparaben (iPrP), methylparaben (MeP), and 4-n-pentylphenol (PeP), as well as the binary mixtures of nPrP with each of the other three antiandrogens. All of the four compounds could exhibit antiandrogenic activity via the hAR. A linear interaction model was applied to quantitatively analyze the interaction between nPrP and each of the other three antiandrogens. The isoboles method was modified to show the variation of combined effects as the concentrations of mixed antiandrogens were changed. Graphs were constructed to show isoeffective curves of three binary mixtures based on the fitted linear interaction model and to evaluate the interaction of the mixed antiandrogens (synergism or antagonism). The combined effect of equimolar combinations of the three mixtures was also considered with the nonlinear isoboles method. The main effect parameters and interaction effect parameters in the linear interaction models of the three mixtures were different from zero. The results showed that any two antiandrogens in their binary mixtures tended to exert equal antiandrogenic activity in the linear concentration ranges. The antiandrogenicity of the binary mixture and the concentration of nPrP were fitted to a sigmoidal model if the concentrations of the other antiandrogens (iPrP, MeP, and PeP) in the mixture were lower than the AR saturation concentrations. Some concave isoboles above the additivity line appeared in all the three mixtures. There were some synergistic effects of the binary mixture of nPrP and MeP at low concentrations in the linear concentration ranges. Interesting, when the antiandrogens concentrations approached the saturation, the interaction between chemicals were antagonistic for all the three mixtures tested. When the toxicity of the three mixtures was assessed using nonlinear isoboles, only antagonism was observed for equimolar combinations of nPrP and iPrP as the concentrations were increased from the no-observed-effect-concentration (NOEC) to effective concentration of 80 %. In addition, the interactions were changed from synergistic to antagonistic as effective concentrations were increased in the equimolar combinations of nPrP and MeP, as well as nPrP and PeP. The combined effects of three binary antiandrogens mixtures in the linear ranges were successfully evaluated by curve fitting and isoboles. The combined effects of specific binary mixtures varied depending on the concentrations of the chemicals in the mixtures. At low concentrations in the linear concentration ranges, there was synergistic interaction existing in the binary mixture of nPrP and MeP. The interaction tended to be antagonistic as the antiandrogens approached saturation concentrations in mixtures of nPrP with each of the other three antiandrogens. The synergistic interaction was also found in the equimolar combinations of nPrP and MeP, as well as nPrP and PeP, at low concentrations with another method of nonlinear isoboles. The mixture activities of binary antiandrogens had a tendency towards antagonism at high concentrations and synergism at low concentrations.     

Nature and prevalence of non-additive toxic effects in industrially relevant mixtures of organic chemicals

The concentration addition (CA) and the independent action (IA) models are widely used for predicting mixture toxicity based on its composition and individual component dose–response profiles. However, the prediction based on these models may be inaccurate due to interaction among mixture components. In this work, the nature and prevalence of non-additive effects were explored for binary, ternary and quaternary mixtures composed of hydrophobic organic compounds (HOCs). The toxicity of each individual component and mixture was determined using the Vibrio fischeri bioluminescence inhibition assay. For each combination of chemicals specified by the 2ⁿ factorial design, the percent deviation of the predicted toxic effect from the measured value was used to characterize mixtures as synergistic (positive deviation) and antagonistic (negative deviation). An arbitrary classification scheme was proposed based on the magnitude of deviation (d) as: additive (10%, class-I) and moderately (10 < d  30%, class-II), highly (30 < d  50%, class-III) and very highly (>50%, class-IV) antagonistic/synergistic. Naphthalene, n-butanol, o-xylene, catechol and p-cresol led to synergism in mixtures while 1, 2, 4-trimethylbenzene and 1, 3-dimethylnaphthalene contributed to antagonism. Most of the mixtures depicted additive or antagonistic effect. Synergism was prominent in some of the mixtures, such as, pulp and paper, textile dyes, and a mixture composed of polynuclear aromatic hydrocarbons. The organic chemical industry mixture depicted the highest abundance of antagonism and least synergism. Mixture toxicity was found to depend on partition coefficient, molecular connectivity index and relative concentration of the components.     

Model-based experimental design for assessing effects of mixtures of chemicals

We exposed flour beetles (Tribolium castaneum) to a mixture of four poly aromatic hydrocarbons (PAHs). The experimental setup was chosen such that the emphasis was on assessing partial effects. We interpreted the effects of the mixture by a process-based model, with a threshold concentration for effects on survival. The behavior of the threshold concentration was one of the key features of this research. We showed that the threshold concentration is shared by toxicants with the same mode of action, which gives a mechanistic explanation for the observation that toxic effects in mixtures may occur in concentration ranges where the individual components do not show effects. Our approach gives reliable predictions of partial effects on survival and allows for a reduction of experimental effort in assessing effects of mixtures, extrapolations to other mixtures, other points in time, or in a wider perspective to other organisms.     

Unexpected effects of sublethal doses of insecticide on the peripheral olfactory response and sexual behavior in a pest insect

Pesticides have long been used as the main solution to limit agricultural pests, but their widespread use resulted in chronic or diffuse environmental pollutions, development of insect resistances, and biodiversity reduction. The effects of low residual doses of these chemical products on organisms that affect both targeted species (crop pests) but also beneficial insects became a major concern, particularly because low doses of pesticides can induce unexpected positive—also called hormetic—effects on insects, leading to surges in pest population growth at greater rate than what would have been observed without pesticide application. The present study aimed to examine the effects of sublethal doses of deltamethrin, one of the most used synthetic pyrethroids, known to present a residual activity and persistence in the environment, on the peripheral olfactory system and sexual behavior of a major pest insect, the cotton leafworm Spodoptera littoralis. We highlighted here a hormetic effect of sublethal dose of deltamethrin on the male responses to sex pheromone, without any modification of their response to host-plant odorants. We also identified several antennal actors potentially involved in this hormetic effect and in the antennal detoxification or antennal stress response of/to deltamethrin exposure.     

UraniumVI sorption behavior on silicate mineral mixtures

UraniumVI sorption experiments involving quartz and clinoptilolite, important mineral phases at the proposed US nuclear waste repository at Yucca Mountain, NV, were conducted to evaluate the ability of surface complexation models to predict UVI sorption onto mineral mixtures based on parameters derived from single-mineral experiments. The experiments were conducted at an initial UVI aqueous concentration of approximately 2.0 x 10(-7) mol.l-1 (0.1 mol.l-1 NaNO3 matrix) and over the pH range approximately 2.5 to approximately 9.5. The UVI solutions were reacted with either quartz or clinoptilolite only, or with mixtures of the two minerals. The experiments were carried out under atmospheric pCO2(g) conditions (in loosely capped containers) or under limited pCO2(g) (in capped containers or in a glove box). Data from sorption experiments on quartz at atmospheric pCO2 conditions were used to derive UVI binding constants for a diffuse-layer surface complexation model (DLM). The DLM was then used with surface area as a scaling factor to predict sorption of UVI onto clinoptilolite and clinoptilolite/quartz mixtures under both atmospheric and low pCO2 conditions. The calculations reproduced many aspects of the pH-dependent sorption behavior. If this approach can be demonstrated for natural mineral assemblages, it may be useful as a relatively simple method for improving radionuclide transport models in performance-assessment calculations.     

A mathematical algorithm to identify toxicity and prioritize pollutants in field sediments

In order to evaluate sediment toxicity, a mathematical algorithm was developed to compute the toxicity of multiple component mixtures acting in an additive manner. A statistical approach was devised to determine the presence of potential interactive effects among mixture components. The algorithm uses three kinds of data to obtain an integrative approach to sediment toxicity assessment: Microtox toxicity data (EC50 values), sediment pollutant concentration measurements, and sequential extraction (SEQ) data to investigate metal partitioning. To simplify the analysis of complex mixtures using a prioritization scheme based on intrinsic toxicity and relative abundance, a toxicity index (TI) was employed as an indicator of adverse ecological impact. In general, the ranking of contaminants using the TI approach was found to be most efficient in reducing computational time, and concentrations using bioavailability data from SEQ was found to be the best theoretical predictor of the experimental mixture toxicity value. Only a few pollutants that were present at the greatest abundance were needed to provide a good approximation of the calculated EC50 found when all components were included. Not only does this substantially reduce the computational time needed to determine the EC50, it could in some cases dramatically reduce the pollutant monitoring effort required to track toxicity effectively. This approach would have substantial implications for both risk assessment and for remediation strategies, making them more efficient by focusing on the priority pollutants identified.     

Fuzzy system models combined with nonlinear regression for daily ground-level ozone predictions

This study focuses on applying a Takagi–Sugeno fuzzy system and a nonlinear regression (NLR) model for ozone predictions in six Kentucky metropolitan areas. The fuzzy “c-means” clustering technique coupled with an optimal output predefuzzification approach (least square method) was used to train the Takagi–Sugeno fuzzy system. The fuzzy system was tuned by specifying the number of rules and the fuzziness factor. The NLR models were based in part on a previously reported, trajectory-based hybrid NLR model that has been used for years for forecasting ground-level ozone in Louisville, KY. The NLR models were each composed of an interactive nonlinear term and several linear terms. Using a common meteorological parameter set as input variables, the NLR models and the Takagi–Sugeno fuzzy systems model exhibited equivalent forecasting performance on test data from 2004. For all 2004 ozone season forecasts for the six metropolitan areas, the mean absolute error was 8.1 ppb for the NLR model and 8.0 ppb for the Takagi–Sugeno fuzzy model. When a nonlinear term (which was part of the NLR model) was included in the fuzzy model, the combined NLR–fuzzy model had slightly better performance than the original NLR model. For all 2004 metropolitan area forecasts, the mean absolute error of the NLR–fuzzy model forecasts was 7.7 ppb. These small differences may be statistically significant, but for practical purposes the performance of the fuzzy models was equivalent to that of the NLR models.     

Potential Impact on Standards for Toxic Air Contaminants

Since the Bhopal incident, the public has placed pressure on regulatory agencies to set community exposure limits for the dozens of chemicals that may be released by manufacturing facilities. More or less objective limits can be established for the vast majority of these chemicals through the use of risk assessment. However, each step of the risk assessment process (i.e., hazard identification, dose-response assessment, exposure assessment, and risk characterization) contains a number of pitfalls that scientists need to avoid to ensure that valid limits are established. For example, in the hazard identification step there has been little discrimination among animal carcinogens with respect to mechanism of action or the epidemiology experience. In the dose-response portion, rarely is the range of “plausible” estimated risks presented. Physiologically based pharmacokinetic (PB-PK) models should be used to understand the difference between the tissue doses and the administered dose, as well as the difference in target tissue concentrations of the toxicant between rodents and humans. Biologically-based models like the Moolgavkar-Knudson-Venzon (MKV) should be developed and used, when appropriate. The exposure assessment step can be significantly improved by using more sensitive and specific sampling and analytical methods, more accurate exposure parameters, and computer models that can account for complex environmental factors. Whenever possible, model predictions of exposure and uptake should be validated by biological monitoring of exposed persons (urine, blood, adipose) or by field measurements of plants, soil, fish, air, or water. In each portion of an assessment, the weight of evidence approach should be used to identify the most defensible value. In the risk characterization, the best estimate of the potential risk as well as the highest plausible risk should be presented. Future assessments would be much improved if quantitative uncertainty analyses were conducted. Procedures are currently available for making future assessments. By correcting some of these shortcomings in how health risk assessments have been conducted, scientists and risk managers should be better able to identify scientifically appropriate ambient air standards and emission limits.     

Stochastic models of oil spill processes

Integrated assessment (IA) is emerging as an approach that is suitable for accommodating the uncertainties and complexities of issues such as climate change, sustainability and lifestyles. With the aim of exploring participatory methodologies within the context of IA, a number of in-depth groups have been conducted in Venice, as part of an EC-funded project called ULYSSES (Urban Lifestyles, Sustainability and Integrated Environmental Assessment). This paper focuses on how technical issues were conveyed to a lay audience through the use of information and communication technology (ICT), namely integrated assessment models. The issues of urban lifestyles and sustainability, particularly in relation to climate change, formed the focus of discussion, the use of ICT being explored during the sessions. We illustrate our major findings with quotations from the participants of the indepth groups, concluding with specifications for new interactive modelling tools to be used in the context of participatory processes.     

An overall risk probability-based method for quantification of synergistic and antagonistic effects in health risk assessment for mixtures: theoretical concepts

Purpose

In the assessment of health risks of environmental pollutants, the method of dose addition and the method of independent action are used to assess mixture effects when no synergistic and/or antagonistic effects are present. Currently, no method exists to quantify synergistic and/or antagonistic effects for mixtures. The purpose of this paper is to develop the theoretical concepts of an overall risk probability (ORP)-based method to quantify the synergistic and antagonistic effects in health risk assessment for mixtures.

Method

The ORP for health effects of environmental chemicals was determined from the cumulative probabilities of exposure and effects. This method was used to calculate the ORP for independent mixtures and for mixtures with synergistic and antagonistic effects.

Results

For the independent mixtures, a mixture ORP can be calculated from the product of the ORPs of individual components. For systems of interacting mixtures, a synergistic coefficient and an antagonistic coefficient were defined respectively to quantify the ORPs of each individual component in the mixture. The component ORPs with synergistic and/or antagonistic effects were then used to calculate the total ORP for the mixture.

Conclusions

An ORP-based method was developed to quantify synergistic and antagonistic effects in health risk assessment for mixtures. This represents a first method to generally quantify mixture effects of interacting toxicants.